class_docstr: Similar to the official `egcn_h.py`. We only consider the node in a timestamp based subgraph,
  so we need to pay attention to `K` should be less than the min node numbers in all subgraph.
  Please refer to section 3.4 of the paper for the formula.
code: def __init__(self, feats, k):
      super().__init__()
      self.scorer = Parameter(torch.Tensor(feats, 1))
      self.reset_parameters()
  
      self.k = k
  
imports: import torch
  import torch.nn
  from dgl.nn.pytorch import GraphConv
  from torch.nn import init
  from torch.nn.parameter import Parameter
label_desc: Use image node_id 1 to create a new TopK object from inherited base classes: torch.nn with example: obj = TopK(feats, k)